In the financial industry, process automation is known to be the most efficient way out of the digitalization dilemma.
Process automation supports companies in coping with current challenges, in terms of both the market and the operational level.
Greater customer commitment is desired, which can only be achieved through an agile market presence and more plentiful customer experience, and through omni-channel products. Robotic and AI approaches help financial companies respond to challenges related to complexity and agility, such as legacy systems, efficiently and with manageable costs.
By automating repetitive routine tasks, companies can efficiently reduce costs and, through process analytics and mining, conduct demand-oriented product management.
Both transparency and auditability can be improved through process automation. As-a-service approaches based on the latter have repeatedly proven their merit when it comes to reducing incurred and, generally, extremely high costs, thanks to the higher accuracy and to optimized risk management, among other factors.
At the process level, financial companies must focus on the front-end processes, especially direct customer operations, on the one hand, and on the back-end processes, especially the integration of legacy and data management systems, on the other, ideally following a trade-off approach in a customer-oriented manner and prioritizing processes on a project basis.
Fact: The digitalization aspiration has increasingly drawn attention away from back-end processes, which are inefficient in many ways. Most of these processes continue to handle high and discrete data volumes through analog means. Such process constellations leave the numerous back-end employees little to no room for innovation or modernization.
Fact: Financial companies must, as part of a comprehensive digitalization strategy, build up an integrated end-to-end process constellation that should allow quick scaling. Without automation, this requires labor difficult to calculate given the complexity and costs, especially on the back-end side.
Besides market-relevant challenges, such as newly emerging sales channels, M&A activities and the corresponding compliance load, ignoring both of these facts has had devastating consequences in the industry, both on an operational level and in terms of profitability:
Introducing RPA involves little to no intervention in the existing system constellation. A short lead time may therefore be assumed, besides the numerous application possibilities. Still, defining an RPA strategy in advance is greatly advisable, in order to determine the scope of use and RPA structures. The main feature of such a strategy is that it does not neglect relevant process dependences.
At the process level, not all activities can be automated, so that the strategy should choose which processes are to be automated and to what degree. Thorough planning prioritized and based on an automation capacity study is therefore essential. Employees should participate both in the RPA strategy and in the RPA application or its development.
Given the aforementioned challenges for digital financial services, the level of automation capacity is a solid argument for a phased and KPI-prioritized introduction of RPA, apart from the need for short ROI cycles:
I now present three examples showing that automation with RPA is not intended to cover the entire sequence of a process and that the level of automation capacity varies from one process to another. Important is to automatize the processes consecutively, so as to display the added value even after a short time.
RPA comprises software solutions for automating rule-based processes and end-to-end activities and leading to increased productivity and improved quality within a short lead time, besides affording employees more time for activities geared to customers and sales. RPA accordingly stands for robot-operated process activities, automating not only routine tasks but more complex business transactions as well, such as the comprehensive tests in software development or even customer communications, in particular identification of individual business transactions and their allocation (routing to chat, call center, cell phone, etc.).
By taking into account automation potential, and with a comprehensive and sustainable strategy, financial companies can achieve the following goals:
Read now: Interview with Prof. August-Wilhelm Scheer on optimization potential from process automation in banking.
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Jalal BelhilaliExpert Process Automation
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